• East Asian mathematical journal
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• v.35 no.3
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• pp.305-318
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• 2019

Over the past decades, the Lee-Carter model [1] has attracted much attention from various demography-related fields in order to project the future mortality rates. In the Lee-Carter model, the speed of mortality improvement is stochastically modeled by the so-called mortality index and is used to forecast the future mortality rates based on the time series analysis. However, the modeling is applied to long time series and thus an important structural change might exist, leading to potentially large long-term forecasting errors. Therefore, in this paper, we are interested in detecting the structural change of the Lee-Carter model and investigating the actuarial implications. For the purpose, we employ the tests proposed by Coelho and Nunes [2] and analyze the mortality data for six countries including Korea since 1970. Also, we calculate life expectancies and whole life insurance premiums by taking into account the structural change found in the Korean male mortality rates. Our empirical result shows that more caution needs to be paid to the Lee-Carter modeling and its actuarial applications.

• Journal of Environmental Health Sciences
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• v.39 no.1
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• pp.19-31
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• 2013

Objectives: Elevated temperatures during summer months have been reported since the early 20th century to be associated with increased daily mortality. However, future death impacts of high temperatures resulting from climate change could be variously estimated in consideration of the future changes in historical temperature-mortality relationships, mortality, and population. This study examined the future death burden of high temperatures resulting from climate change in Seoul over the period of 2001-2040. Methods: We calculated yearly death burden attributable to high temperatures stemming from climate change in Seoul from 2001-2040. These future death burdens from high temperature were computed by multiplying relative risk, temperature, mortality, and population at any future point. To incorporate adaptation, we assumed future changes in temperature-mortality relationships (i.e. threshold temperatures and slopes), which were estimated as short-term temperature effects using a Poisson regression model. Results: The results show that climate change will lead to a substantial increase in summer high temperature-related death burden in the future, even considering adaptation by the population group. The yearly death burden attributable to elevated temperatures ranged from approximately 0.7 deaths per 100,000 people in 2001-2010 to about 1.5 deaths per 100,000 people in Seoul in 2036-2040. Conclusions: This study suggests that adaptation strategies and communication regarding future health risks stemming from climate change are necessary for the public and for the political leadership of South Korea.

• Journal of Environmental Health Sciences
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• v.37 no.6
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• pp.397-405
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• 2011

Objectives: The impact of climate change on the health has been of increasing concern due to a recent temperature increase and weather abnormality, and the research results of the impact varied depending on regions. We synthesized risk estimates of the overall health effects of low and high temperature taking account of the heterogeneity. Methods: A comprehensive literature search was conducted using PUBMED to identify journal articles of low and/or high temperature effects on mortality. The search was limited to the English language and epidemiological studies using time-series analysis and/or case-crossover design. Random-effect models in meta analysis were used to estimate the percent increase in mortality with $1^{\circ}C$ temperature decrease or increase with 95% confidence intervals (CI) in cold or hot days. Results: Twenty three studies were presented in two tables: 1) low temperature effects; 2) high temperature effects on mortality. The combined effects of low and high temperatures on total mortality were 2% (95% CI, 1-4%) per $1^{\circ}C$ decrease and 4% (95% CI, 2-5%) per $1^{\circ}C$ increase of temperature, respectively. Conclusions: This meta analysis found that both low and high temperatures affected mortality, and the magnitude of high temperature appeared to be stronger than that of low temperature.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.10
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• pp.5003-5006
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• 2012

Objective: Yanting County is a high risk area for esophageal cancer (EC) in China. The purpose of this study was to describe the mortality and mortality change of EC from 2004 to 2009 in Yanting County. Methods: EC mortality data from 2004 to 2009 obtained from the Cancer Registry in Yanting were analyzed. Annual percentage changes (APC) were calculated to assess the trends in EC mortality. Age-standardized mortality was calculated based on world standard population of 2000. Results: The average EC mortality was 54.7/$10^5$ in males and 31.6/$10^5$ in females over the 6 years. A decline in EC mortality with time was observed in both genders, with a rate of -8.70% per year (95% CI: -13.23%~-3.93%) in females and -4.11% per year (95%CI: -11.16%~3.50%) in males. Conclusion: EC mortality decreased over the six years in both genders, although it remained high in the Yanting area. There is still a need to carry out studies of risk factors for improved cancer prevention and further reduction in the disease burden.

• Journal of Environmental Impact Assessment
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• v.21 no.1
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• pp.71-80
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• 2012

Against the backdrop of the clear impact of climate change, it has become essential to analyze the influence of climate change and relevant vulnerabilities. This research involved evaluating the impact of heat waves in Seoul, from among many local autonomous bodies that are responsible for implementing measures on adapting to climate change. To carry out the evaluation, the A1B scenario was used to forecast future temperature levels. Future climate scenario results were downscaled to $1km{\times}1km$ to result in the incorporation of regional characteristics. In assessing the influence of heat waves on people-especially the excess mortality-we analyzed critical temperature levels that affect excess mortality and came up with the excess mortality. Results of this evaluation on the impact of climate change and vulnerabilities indicate that the number of days on which the daily average temperature reaches $28.1^{\circ}C$-the critical temperature for excess mortality-in Seoul will sharply increase in the 2050s and 2090s. The highest level of impact will be in the month of August. The most affected areas in the summer will be Songpa-gu, Gangnam-gu, and Yeongdeungpo-gu. These areas have a high concentration of residences which means that heat island effects are one of the reasons for the high level of impact. The excess mortality from heat waves is expected to be at least five times the current figure in 2090. Adaptation plan needs to be made on drawing up long-term adaptation measures as well as implementing short-term measures to minimize or adapt the impact of climate change.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2067-2070
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• 2013

Background/Aim: Stomach cancer is the second most common cause of death from all malignant tumors in the world (third in men, fifth in women), with a strong decreasing trend in most developed countries. The aim of this descriptive epidemiological study was to analyze mortality of stomach cancer in Serbia, excluding the Province of Kosovo, in the 1991-2009 period. Materials and Methods: In data analysis, we used mortality rates which were standardized directly using those of the world population as a standard. In order to analyze the mortality trend from stomach cancer, linear trend and regression analysis were used. Confidence intervals (CIs) for the average age-adjusted and age-specific mortality rates were assessed with 95% level of probability. Mortality data were derived from the data file of the Statistical Office of the Republic of Serbia. Results: During the 1991-2009 period, a significant downward trend in mortality of stomach cancer was recorded in Serbia (y=9.78 - 0.13x, p=0.000; average annual percent change was -6.3 (95%CI, -7.8 to - 4.8). During the same period, a significant decrease in mortality trend was found both in male (y=14.13 - 0.20x; p=0.000; % change was -7.7 (95%CI, -10.9 to -4.5) and female populations (y=6.27 - 0.08x; p=0.000; % change was - 4.4 (95%CI, -5.3 to -3.6). Conclusion: Decreasing trends in mortality from stomach cancer in Serbia are similar to those in most developed countries.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7569-7573
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• 2014

The main objective of this study was to analyze the mortality trends of female breast cancer in Turkey between the years 1987-2008. The rates per 100,000 age-standardized to the European standard population were assessed and time trends presented using joinpoint regression analysis. Average annual percent change (AAPC), anual percent change (APC) and 95% confidence interval (CI) was calculated. Nearly 23,000 breast cancer deaths occurred in Turkey during the period 1987-2008, with the average annual age-standardized mortality rate (ASR) being 11.9 per 100,000 women. In the last five years, significant increases were observed in all age groups, but there was no significant change over the age of 65. In this period, the biggest significant increase was in the 45-54 age group (AAPC=4.3, 95%CI=2.6 to 6.0).

• Communications for Statistical Applications and Methods
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• v.28 no.3
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• pp.233-250
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• 2021

This paper studies if the accuracies of mortality models (LC model vs. 4-parametric model) are aggravated if a mortality structure changes due to the impact of COVID-19. LC model (LCM) uses dimension reduction for fitting to the log mortality matrix so that the performance of the dimension reduction method may not be good when the matrix structure changes. On the other hand, 4-parametric factor model (4-PFM) is designed to use factors for fitting to log mortality data by age groups so that it would be less affected by the change of the mortality structure. In fact, the forecast accuracies of LCM are better than those of 4-PFM when life-tables are used whereas those of 4-PFM are better when the mortality structure changes. Thus this result shows that 4-PFM is more reliable in performance to the structural changes of the mortality. To support the accuracy changes of LCM the functional aspect is explained by computing eigenvalues produced by singular vector decomposition

• Korea journal of population studies
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• v.9 no.2
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• pp.53-66
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• 1986

This study was carried out to determine the mortality level and it's related demographic factors in Korea since 1942. In order to clarify the changes in structure of mortality and the causes of death, the indices such as Crude Death Rate(CDR) or Life Expectancy at Birth were used. The author examined the mortality levels and major causes of death and performed the relevant demographic analysis. The followings are the summary of this study: 1. The CDR declined rapidly till 1960's. Such improvement slowed down from 1960's to mid 1970's and stabilized afterwards. It was due to the change of age composition, namely, the increase of aging population. 2. The Life Expectancy at Birth increased rapidly till mid 1960's. But elongation of the Life Expectancy slowed down after then. Especially in female, it slowed down more. 3. Changing patterns of major causes of death summarize that, till 1960's infectious diseases were major causes of death, but recently non-infectious diseases like chronic degenerative diseases became more prevalent. 4. The elongation of Life Expectancy at Birth till mid 1960's was mainly resulted by $_4{q}_1$. But the major contributing factor of the improvement in Life Expectancy at Birth in female is he reduction of $_$\infty${q}_{50}$ recently. In male, the improvement in Life Expectancy at Birth is due to the reduction of $_1{q}_0$. recently. 5. The age-sex-specific mortality rates revealed that $_n{q}_x$ declined in common throughout the period, even though there exists some variability of their ranges as age changes. Consequently, this study seems to suggest that the demographic transition in Korea occurred between late 1960's and early 1970's. In other words, the rapid change before late 1960's was eased in early 1970's. The slow change in this period caused a stabilizing pattern. Therefore, the population change is expected to be stabilized continuously.

• Journal of Environmental Health Sciences
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• v.36 no.1
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• pp.20-26
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• 2010

Temperature change has been shown to affect daily mortality even though different analytical methods produce different results. The effect of air pollution on the relationship between the temperature and the mortality is not large, although differences exist between temperature models. The aim of this study was to examine how the temperature change affected the daily mortality in Seoul by comparing the results from the temperature model using two study periods: one from 1994 to 2007 and the other from 1997 to 2007. Generally mean temperature, minimum temperature and Q10 temperature was derived as an optimal model, even though there are differences between age and cause of death. The analysis of threshold using total mortalities in all ages from 1994 to 2007 and from 1997 to 2007 showed that the number of the deaths increased 7.02% (95% CI: 6.06~7.98) and 2.51% (95% CI: 1.83~3.19), respectively as the mean temperature increased $1^{\circ}C$ from a threshold temperature of $27.5^{\circ}C$ and $25.7^{\circ}C$ respectively. These results indicated that the temperature has less effect on the number of death than does an extreme heat wave period.